计算机科学
语音识别
航程(航空)
集合(抽象数据类型)
言语感知
语音学
理解力
演讲制作
信号(编程语言)
领域(数学分析)
过程(计算)
自然语言处理
感知
人工智能
语言学
心理学
数学
工程类
数学分析
哲学
航空航天工程
神经科学
程序设计语言
操作系统
作者
Jessie S. Nixon,Fabian Tomaschek
标识
DOI:10.1002/9781119839859.ch9
摘要
This chapter reviews the arguments that have been raised against the unit-based account and presents some of the wide range of approaches that have been taken to modelling speech which do not involve speech units. Introductions to phonetics demonstrate that the speech signal consists of fluctuations in energy that occur over time in a wide range of frequencies. The chapter presents the evidence and arguments against the combinatorial approach. A small set of phonemes or distinctive features seemingly provides a way to tame the wild, complex, and unpredictable nature of the continuous speech signal. Proponents of distributional models argue that what is learned is the statistical distribution of phonetic cues. Linguistic representations and processes emerge through a predictive, error-driven discrimination process and therefore adapt to surprising events or information. Most studies on speech perception and word recognition have focused on the phonetic domain.
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